Project Summary/Abstract Candidate Background: In graduate school at the University of Virginia, I built on my undergraduate spectroscopy education by using spectroscopic tools to investigate membrane protein flexibility. As a Postdoctoral Fellow at Vanderbilt, I transitioned to membrane protein structural biology involved in human disease, specifically KCNQ and KCNE family-associated channelopathies. As a Postdoctoral Fellow, I have been involved in several projects concerning the structural underpinnings of disease mechanisms, most recently proposing a mechanism for diminished apical chloride secretion through an estrogen-induced loss of KCNQ1- KCNE3 channel conduction. Research Strategy: The human voltage-gated sodium channel Nav1.5 (encoded by SCN5A) is implicated in several diseases of the heart including dilated cardiomyopathy, cardiac conduction disease, sick sinus syndrome, type 3 longQT syndrome, and Brugada syndrome. Several algorithms accurately predict SCN5A variants that are ultimately harmful (SIFT, PolyPhen-2, PredSNP, etc.). However, there is a significant gap in the negative predictive ability of these methods, i.e. the ability to accurately classify a variant as benign. The approach I am proposing is to tackle this problem on two fronts: 1) incorporating channel-specific, quantitative information-rich data into predictive model construction?the objective being to predict channel function, instead of disease- inducing propensity?and 2) including a set of point mutation variants enriched in WT/neutral phenotypes to improve discrimination power during model training and evaluation. This project aims to ultimately predict Nav1.5 channel phenotypes for all possible amino-acid changing single nucleotide polymorphisms (nsSNP) by balancing high-throughput computation and rigorous experimental validation with model systems: predicting the nearly 15,000 possible SCN5A missense nsSNPs is currently only feasible in silico, i.e. leveraging calculable channel-specific protein sequence and structure-based features. The availability of a high-throughput electrophysiology instrument allows for an unprecedented amassing of ion channel functional output from heterologously expressed Nav1.5; the evaluation of SCN5A variants impact on action potential in the more native like human induced pluripotent stem cell cardiomyocytes is possible in low-throughput. During the mentored (K99) phase of this award, I will generate (mis)trafficking and electrophysiology current output data from missense nsSNPs of SCN5A, focusing on the Voltage-Sensing Module (VSM) of domain IV (Aim 1) and train an SCN5A VSM IV-specific phenotype prediction model using trafficking and electrophysiology data from Aim 1 and the literature (Aim 2). As an independent investigator, I will determine structure and flexibility-induced changes from selected variants using a combination of Rosetta modeling and nuclear magnetic resonance (NMR) to refine the predictive model (Aim 3). Career Development and Training: My training proposal is ambitious covering several disciplines, some of which will be new to me. The skills I will acquire are developing computational predictive models of ion channel phenotypes, trafficking/expression quantitation through Fluorescence Activated Cell Sorting (FACS), CRISPR/Cas9 gene manipulation, and hiPSC cardiomyocyte production. Though there are many activities planned, I will be trained directly in the laboratories of prominent scientists in their respective fields: Charles Sanders, Jens Meiler, and Dan Roden.